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Flooding is widely recognized as a global threat, due to the extent and magnitude of damage it causes around the world each year. Reducing flood risk and improving flood resilience are two closely related aspects of flood management. This book presents the latest advances in flood risk and resilience management on the following themes: hazard and risk analysis, flood behaviour analysis, assessment frameworks and metrics and intervention strategies. It can help the reader to understand the current challenges in flood management and the development of sustainable flood management interventions to reduce the social, economic and environmental consequences from flooding.

nonstationarity --- univariate model --- GAMLSS --- bivariate model --- copulas --- floodway --- optimization --- particle swarm optimization --- HEC-RAS --- flood mitigation --- hydraulic modeling --- flood risk perception --- natural flood management --- disaster mitigation --- flood-prone city --- questionnaire survey --- flood hazard --- land use --- urban growth --- Villahermosa --- architecture modelling flood resilience --- resilience engineering --- system-of-systems water systems --- multi-risk matrix --- resilience --- flood risk --- multi-hazard --- risk reduction --- flood resilience index --- flood resilience analysis --- urban floods --- flood risk assessment --- flood inundation modelling --- Artificial Intelligence --- machine learning --- flood --- preparedness --- flood resilience --- blue-green infrastructure --- flood risk management --- sustainable --- drainage systems --- systems --- flood control materials --- intelligent warehousing --- location allocation --- multi-objective optimization --- drone applications --- deployment time --- monitoring --- flood modelling --- evacuation --- rescue --- management strategy --- metrics

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The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies.

cloud computing --- container orchestration --- custom metrics --- Docker --- edge computing --- Horizontal Pod Autoscaling (HPA) --- Kubernetes --- Prometheus --- resource metrics --- fog computing --- task allocation --- multi-objective optimization --- evolutionary genetics --- hyper-angle --- crowding distance --- containers --- leader election --- load balancing --- stateful --- multi-access edge computing --- orchestrator --- task offloading --- fuzzy logic --- 5G --- fog/edge computing --- service provisioning --- service placement --- service offloading --- Internet of Things (IoT) --- task scheduling --- markov decision process (MDP) --- deep reinforcement learning (DRL) --- resource management --- algorithm classification --- evaluation framework --- web --- Web Assembly --- OpenCL --- LWC --- fast implementation --- Internet of things --- IoT actor --- data manager --- GDPR --- computing --- computational offloading --- dynamic offloading threshold --- minimizing delay --- minimizing energy consumption --- maximizing throughputs --- n/a

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This second Special Issue connects both the fundamental and application aspects of thermomechanical machines and processes. Among them, engines have the largest place (Diesel, Lenoir, Brayton, Stirling), even if their environmental aspects are questionable for the future. Mechanical and chemical processes as well as quantum processes that could be important in the near future are considered from a thermodynamical point of view as well as for applications and their relevance to quantum thermodynamics. New insights are reported regarding more classical approaches: Finite Time Thermodynamics F.T.T.; Finite Speed thermodynamics F.S.T.; Finite Dimensions Optimal Thermodynamics F.D.O.T. The evolution of the research resulting from this second Special Issue ranges from basic cycles to complex systems and the development of various new branches of thermodynamics.

combined cycle --- inverse Brayton cycle --- regenerative Brayton cycle --- power output --- thermal efficiency --- finite time thermodynamics --- closed simple Brayton cycle --- power density --- ecological function --- multi-objective optimization --- quantum thermodynamics --- quantum circuit --- open quantum system --- isothermal process --- IBM quantum computer --- Stirling refrigerator --- thermodynamic analysis --- numerical model --- imperfect regeneration --- irreversible Lenoir cycle --- cycle power --- heat conductance distribution --- performance optimization --- irreversible Carnot engine --- optimization --- thermodynamics with finite speed --- internal and external irreversibilities --- entropy generation calculation --- thermodynamics in finite time --- irreversible Diesel cycle --- Carnot cycle --- Carnot efficiency --- thermal entropy --- chemical entropy --- mechanical entropy --- thermal exergy --- chemical exergy --- mechanical exergy --- metabolic reactions --- Carnot engine --- Chambadal model --- entropy production action --- efficiency at maximum power --- n/a

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The book deals with the latest research on membrane distillation. New membrane and module designs, low-temperature applications, integration with other membrane units and pilot scale investigations are presented and discussed.

Technology: general issues --- FGD wastewater --- integrated membrane-based process --- zero liquid-discharge --- sustainability --- bioethanol --- sweeping gas membrane distillation --- SGMD --- glucose --- permeate flux --- optimization --- membrane distillation --- triple layer composite membrane --- highly concentrated solutions --- PVDF --- PES --- membrane stability --- polypropylene --- TIPS --- talc --- desalination --- brine treatment --- pilot scale --- permeate quality --- membrane filtration --- high salinity --- spacer-filled channel --- temperature polarization --- computational fluid dynamics --- thermochromic liquid crystals --- distillation --- high recovery rate --- brine concentration --- zero liquid discharge --- membrane distillation module --- wastewater concentration --- resource recovery --- 1,3-dimethyl-2-imidazolidinone --- solvent dehydration --- hollow-fiber membrane --- multi-objective optimization --- submerged module --- capillary membrane --- direct contact membrane distillation --- urea --- low temperature --- composite membrane --- plasma-polymerized hydrophobic fluorosiloxane coating --- hydrophilic porous hollow-fiber substrate

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Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass customization); and from agent-based manufacturing (2000s) to cloud manufacturing (2010s) (both deploying the value stream complexity into the material and information flow, respectively). The next natural evolutionary step is to provide value by creating industrial cyber-physical assets with human-like intelligence. This will only be possible by further integrating strategic smart sensor technology into the manufacturing cyber-physical value creating processes in which industrial equipment is monitored and controlled for analyzing compression, temperature, moisture, vibrations, and performance. For instance, in the new wave of the ‘Industrial Internet of Things’ (IIoT), smart sensors will enable the development of new applications by interconnecting software, machines, and humans throughout the manufacturing process, thus enabling suppliers and manufacturers to rapidly respond to changing standards. This reprint of “Sense and Respond” aims to cover recent developments in the field of industrial applications, especially smart sensor technologies that increase the productivity, quality, reliability, and safety of industrial cyber-physical value-creating processes.

Technology: general issues --- History of engineering & technology --- EEG sensors --- manufacturing systems --- problem-solving --- deep learning --- TDOA --- sensor networks --- hyperboloids --- node distribution --- genetic algorithms --- asynchronous --- Cramér–Rao lower bound --- heteroscedasticity --- soft sensors --- industrial optical quality inspection --- artificial vision --- long-term monitoring benefits --- indoor air quality --- low cost --- occupational safety and health --- industry 4.0 --- IOTA tangle --- Industry 4.0 --- IIoT --- geometric deep learning --- lean management --- cramer rao lower bound --- localization --- LPS --- multi-objective optimization --- sensor failure --- wireless sensor networks --- conceptual framework --- sensors --- approaches --- tools --- data --- application --- project engineering --- LCA --- SDG 9 --- SDG 11